Fetching the paper…
Reading the bibliography…
An interpretable system for open-domain reasoning needs to express its reasoning process in a transparent form.
Natural language input for a computer problem solving system
Daniel G. Bobrow. 1964 · 1964
Earlier work this paper cites.
Procedures as a representation of data in a computer program for understanding natural language
Terry Winograd. 1971 · 1971
Earlier work this paper cites.
Automatic acquisition of hyponyms from large text corpora
Marti A. Hearst. 1992 · 1992
Earlier work this paper cites.
Reasoning with Polarity in Categorial Type Logic
Raffaella Bernardi. 2002 · 2002
Earlier work this paper cites.
Explaining question answering models through text generation
Veronica Latcinnik and Jonathan Berant. 2020 · 2004
Earlier work this paper cites.
A ‘natural logic’ inference system using the Lambek calculus
Anna Zamansky, Nissim Francez, and Yoad Winter. 2006 · 2006
Earlier work this paper cites.
Critical thinking for language models
Gregor Betz, Christian Voigt, and Kyle Richardson. 2020 · 2009
Earlier work this paper cites.
An extended model of natural logic
Bill MacCartney and Christopher D. Manning. 2009 · 2009
Earlier work this paper cites.
Satisfiability modulo theories: Introduction and applications
Leonardo De Moura and Nikolaj Bjørner. 2011 · 2011
Earlier work this paper cites.
Natural language inference in context – investigating contextual reasoning over long texts
Hanmeng Liu, Leyang Cui, Jian Liu, and Yue Zhang. 2020 · 2011
Earlier work this paper cites.
A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
Earlier work this paper cites.
Combining natural logic and shallow reasoning for question answering
Gabor Angeli, Neha Nayak, and Christopher D. Manning. 2016 · 2016
Earlier work this paper cites.
Improving neural machine translation models with monolingual data
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
Earlier work this paper cites.
A monotonicity calculus and its completeness
Thomas Icard, Lawrence Moss, and William Tune. 2017 · 2017
Earlier work this paper cites.
Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel Bowman, and Noah A. Smith. 2018 · 2018
Earlier work this paper cites.
Stress test evaluation for natural language inference
Aakanksha Naik, Abhilasha Ravichander, Norman Sadeh, Carolyn Rose, and Graham Neubig. 2018 · 2018
Earlier work this paper cites.
Hypothesis only baselines in natural language inference
Adam Poliak, Jason Naradowsky, Aparajita Haldar, Rachel Rudinger, and Benjamin Van Durme. 2018 · 2018
Earlier work this paper cites.
Constructing datasets for multi-hop reading comprehension across documents
Johannes Welbl, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
Cited alongside, same era.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
Cited alongside, same era.
HotpotQA: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018 · 2018
Cited alongside, same era.
Understanding dataset design choices for multi-hop reasoning
Jifan Chen and Greg Durrett. 2019 · 2019
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
Cited alongside, same era.
Compositional questions do not necessitate multi-hop reasoning
Sewon Min, Eric Wallace, Sameer Singh, Matt Gardner, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2019 · 2019
BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Later among the works it cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
Later among the works it cites.
PRover: Proof generation for interpretable reasoning over rules
Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava, and Mohit Bansal. 2020 · 2020
Later among the works it cites.
BLEURT: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur Parikh. 2020 · 2020
Later among the works it cites.
Unsupervised commonsense question answering with self-talk
Vered Shwartz, Peter West, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2020 · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Explain Yourself! Leveraging Language Models for Commonsense Reasoning
Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
Cited alongside, same era.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Cynthia Rudin. 2019 · 2019
Cited alongside, same era.
NLProlog: Reasoning with weak unification for question answering in natural language
Leon Weber, Pasquale Minervini, Jannes Münchmeyer, Ulf Leser, and Tim Rocktäschel. 2019 · 2019
Cited alongside, same era.
Autoregressive reasoning over chains of facts with transformers
Ruben Cartuyvels, Graham Spinks, and Marie-Francine Moens. 2020 · 2020
Cited alongside, same era.
Transformers as soft reasoners over language
Peter Clark, Oyvind Tafjord, and Kyle Richardson. 2020 · 2020
Cited alongside, same era.
Leap-of-thought: Teaching pre-trained models to systematically reason over implicit knowledge
Alon Talmor, Oyvind Tafjord, Peter Clark, Yoav Goldberg, and Jonathan Berant. 2020 · 2020
Later among the works it cites.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Later among the works it cites.
WorldTree v2: A corpus of science-domain structured explanations and inference patterns supporting multi-hop inference
Zhengnan Xie, Sebastian Thiem, Jaycie Martin, Elizabeth Wainwright, Steven Marmorstein, and Peter Jansen. 2020 · 2020
Later among the works it cites.
ReClor: A reading comprehension dataset requiring logical reasoning
Weihao Yu, Zihang Jiang, Yanfei Dong, and Jiashi Feng. 2020 · 2020
Later among the works it cites.
PEGASUS: Pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter Liu. 2020 · 2020
Later among the works it cites.
Towards robustifying NLI models against lexical dataset biases
Xiang Zhou and Mohit Bansal. 2020 · 2020
Later among the works it cites.
Conversational neuro-symbolic commonsense reasoning
Forough Arabshahi, Jennifer Lee, Mikayla Gawarecki, Kathryn Mazaitis, Amos Azaria, and Tom Mitchell. 2021 · 2021
Closest in time.
Thinking Aloud: Dynamic Context Generation Improves Zero-Shot Reasoning Performance of GPT-2
Gregor Betz, Kyle Richardson, and Christian Voigt. 2021 · 2021
Closest in time.
Explaining answers with entailment trees
Bhavana Dalvi, Peter A. Jansen, Oyvind Tafjord, Zhengnan Xie, Hannah Smith, Leighanna Pipatanangkura, and Peter Clark. 2021 · 2021
Closest in time.
Text modular networks: Learning to decompose tasks in the language of existing models
Tushar Khot, Daniel Khashabi, Kyle Richardson, Peter Clark, and Ashish Sabharwal. 2021 · 2021
Closest in time.
ProofWriter: Generating implications, proofs, and abductive statements over natural language
Oyvind Tafjord, Bhavana Dalvi, and Peter Clark. 2021 · 2021
Closest in time.